Multiagent Learning and Adaptation in an Information Filtering Market

Adaptation, Coevolution, and Learning in Multiagent Systems

Volume

Papers from the 1996 AAAI Spring Symposium

Contents

This paper presents an adaptive model for multiagent coordination based on the metaphor of economic markets. This model has been used to develop SIGMA, a system for filtering Usenet netnews which is able to cope with the non-stationary and partially observable nature of the information filtering task at hand. SIGMA integrates a number of different learning and adaptation techniques, including reinforcement learning, bidding price adjustment, and relevance feedback. Aspects of these are discussed below.